---
license: apache-2.0
widget:
- text: I'm fine. Who is this?
- text: You can't take anything seriously.
- text: In the end he's going to croak, isn't he?
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-gest-pred-seqeval-partialmatch
  results: []
datasets:
- Jsevisal/gesture_pred
pipeline_tag: token-classification
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-gest-pred-seqeval-partialmatch

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7270
- Precision: 0.771293
- Recall: 0.720130	
- F1: 0.727670
- Accuracy: 0.819896

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8976        | 1.0   | 147  | 1.1361          | 0.4802    | 0.4141 | 0.4034 | 0.7009   |
| 0.916         | 2.0   | 294  | 0.8206          | 0.6045    | 0.5622 | 0.5493 | 0.7744   |
| 0.5893        | 3.0   | 441  | 0.7711          | 0.7318    | 0.6613 | 0.6747 | 0.7952   |
| 0.4019        | 4.0   | 588  | 0.7270          | 0.7713    | 0.7201 | 0.7277 | 0.8199   |
| 0.2713        | 5.0   | 735  | 0.7353          | 0.8000    | 0.7512 | 0.7545 | 0.8349   |
| 0.1831        | 6.0   | 882  | 0.7802          | 0.7958    | 0.7245 | 0.7375 | 0.8303   |
| 0.1343        | 7.0   | 1029 | 0.7785          | 0.7652    | 0.7351 | 0.7204 | 0.8362   |
| 0.0989        | 8.0   | 1176 | 0.8017          | 0.7753    | 0.7317 | 0.7313 | 0.8322   |
| 0.079         | 9.0   | 1323 | 0.8281          | 0.7844    | 0.7297 | 0.7325 | 0.8349   |
| 0.0673        | 10.0  | 1470 | 0.8238          | 0.7765    | 0.7347 | 0.7289 | 0.8355   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2